Delete data/COPA-ca.py

data/COPA-ca.py

@@ -1,92 +0,0 @@
-# Loading script for the COPA-ca dataset.
-import json
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = ""
-
-_DESCRIPTION = """\
-               The COPA-ca dataset (Choice of plausible alternatives in Catalan) is a professional translation of the English COPA dataset into Catalan, commissioned by BSC LangTech Unit. The dataset consists of 1000 premises, each given a question and two choices with a label encoding which of the choices is more plausible given the annotator.
-
-The dataset is split into 400 training samples, 100 validation samples, and 500 test samples. It includes the following features: 'premise', 'choice1', 'choice2', 'label', 'question', 'changed' (boolean).
-
-This work is licensed under a Attribution-ShareAlike 4.0 International License.
-               """
-
-_HOMEPAGE = "https://zenodo.org/record/8124398"
-
-
-_URL = "https://huggingface.co/datasets/projecte-aina/copa-ca/resolve/main/"
-_TRAIN_FILE = "copa-ca.train.jsonl"
-_DEV_FILE = "copa-ca.val.jsonl"
-_TEST_FILE = "copa-ca.test.jsonl"
-
-
-class copaCaConfig(datasets.BuilderConfig):
-    """ Builder config for the COPA-ca dataset """
-
-    def __init__(self, **kwargs):
-        """BuilderConfig for COPA-ca.
-        Args:
-          **kwargs: keyword arguments forwarded to super.
-        """
-        super(copaCaConfig, self).__init__(**kwargs)
-        
-class copaCa(datasets.GeneratorBasedBuilder):
-    """ COPA-ca Dataset """
-
-    BUILDER_CONFIGS = [
-        copaCaConfig(
-            name="copa-ca",
-            version=datasets.Version("1.0.1"),
-            description="COPA-ca dataset",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "premise": datasets.Value("string"),
-                    "choice1": datasets.Value("string"),
-                    "choice2": datasets.Value("string"),
-                    "question": datasets.Value("string"),
-                    'label': datasets.features.ClassLabel(names=['1', '2']),
-                    "idx": datasets.Value("int64"),
-                    "changed": datasets.Value("bool"),
-                }
-            ),
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        urls_to_download = {
-            "train": f"{_URL}{_TRAIN_FILE}",
-            "dev": f"{_URL}{_DEV_FILE}",
-            "test": f"{_URL}{_TEST_FILE}",
-        }
-        downloaded_files = dl_manager.download_and_extract(urls_to_download)
-
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding='utf-8') as f:
-            for i, line in enumerate(f):
-                data = json.loads(line)
-                yield i, {
-                    'premise': data['premise'],
-                    'choice1': data['choice1'],
-                    'choice2': data['choice2'],
-                    'question': data['question'],
-                    'label': str(data['label']),
-                    'idx': data['idx'],
-                    'changed': data['changed']
-                }